[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["필요한 정보가 없음","missingTheInformationINeed","thumb-down"],["너무 복잡함/단계 수가 너무 많음","tooComplicatedTooManySteps","thumb-down"],["오래됨","outOfDate","thumb-down"],["번역 문제","translationIssue","thumb-down"],["샘플/코드 문제","samplesCodeIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-01-03(UTC)"],[[["Models ingest data through floating-point arrays called feature vectors, which are derived from dataset features."],["Feature vectors often utilize processed or transformed values instead of raw dataset values to enhance model learning."],["Feature engineering is the crucial process of converting raw data into suitable representations for the model, encompassing techniques like normalization and binning."],["Non-numerical data like strings must be converted into numerical values for use in feature vectors, a key aspect of feature engineering."]]],[]]